Add software-based CAM retrieval benchmark to compare retrieval quality
and speed against hardware simulation. Includes experiment documentation
with noise sweep analysis on CIFAR-10/100 datasets.
- Add sw_retrieval_benchmark.py for software Hamming distance Top-K retrieval
- Add test_sw_retrieval_benchmark.py with unit tests for dataset loading and metrics
- Add experiment doc (sw_hw_cam_retrieval_benchmark.md) comparing software vs hardware
- Document noise sweep impact on retrieval quality at various WRITE_NOISE_RATE values
- Rename `read_noise` scenarios and noise_mode to `read_pass_through` across
run_cam_correctness.py, test_run_cam_correctness.py, and Makefiles
- Update RTL comment in match_engine_pipeline.sv to reflect pass-through behavior
- Move unit-level cocotb tests from `tests.test_*` flat namespace to
`tests.modules.*` and `tests.top.*` subdirectory layout, matching actual
Makefile paths (hw/sim/tests/modules/..., hw/sim/tests/top/...)
- Remove redundant dual-noise subtarget from read_noise/Makefile
- Update help text and docs to reflect read-path pass-through semantics
- Add .codegraph to .gitignore
- Make cam_read_noise a pass-through module, removing all noise injection logic
- Switch write noise to use noise_mask_bernoulli instead of noise_mask_grouped
- Add state machine to cam_write_noise for mask generation timing
- Remove noise_mask_grouped.sv (no longer needed)
- Remove read noise parameters from cam_noisy and cam_top
- Update simulation and benchmark code to reflect read noise removal
- Sync documentation to reflect Phase 2 architecture
